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Set Relations in Social Research: Evaluating Their Consistency and Coverage
Abstract
Because of its inherently asymmetric nature, set-theoretic analysis offers many interesting contrasts with analysis based on correlations. Until recently, however, social scientists have been slow to embrace set-theoretic approaches. The perception was that this type of analysis is restricted to primitive, binary variables and that it has little or no tolerance for error. With the advent of “fuzzy” sets and the recognition that even rough set-theoretic relations are relevant to theory, these old barriers have crumbled. This paper advances the set-theoretic approach by presenting simple descriptive measures that can be used to evaluate set-theoretic relationships, especially relations between fuzzy sets. The first measure, “consistency,” assesses the degree to which a subset relation has been approximated, whereas the second measure, “coverage,” assesses the empirical relevance of a consistent subset. This paper demonstrates further that set-theoretic coverage can be partitioned in a manner somewhat analogous to the partitioning of explained variation in multiple regression analysis.
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“Relatedly, Ragin (2006, 304) suggests using 'consistency' (i.e., the share of cases having the same combination of conditions that also display the outcome) as a useful criterion”
From Qualitative Comparative Analysis: How Inductive Use and Measurement Error Lead to Problematic Inference (2013) · cites this paper as Ragin (2006, 304)
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“In this study, we used the four-value coding scheme defined by Ragin (2008), for which the values are 0, 0.”
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“Conversely, cases where the outcome is not present are irrelevant and are thus absent when testing propositions (Ragin 2006, p. 293).”
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“Coverage provides information on the relevance of conditions for outcome, an analogous measure of R 2 in regression analysis (Ragin, 2006; Mendel & Korjani, 2012).”
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“The coverage of each configuration provides evidence of its relative empirical importance (Ragin, 2006).”
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“…capable of generating CRX and CRB. fsQCA is a set-theoretical technique, which uses Boolean algebra to identify a series of sufficient conditions (also called causal configurations and recipes ) to predict an outcome (Gannon et al., 2019; Ragin, 2006; Rasoolimanesh, Ringle, Sarstedt, & Olya, 2021).”
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Metadata
- Authors
- Ragin, C. C.
- Affiliations
- University of Arizona (US)
- Corresponding author
- Ragin, Charles C.
- ORCID
- Ragin, Charles C.
- Venue
- Political Analysis
- Publisher
- Cambridge University Press (CUP)
- Published
- 2006
- Volume
- 14
- Issue
- 3
- Pages
- 291-310
- ISSN
- 1047-1987 (ISSN-L)
- 1476-4989
- OpenAlex
- W2150935468
- Cited by
- 1,784
- References
- 20
- Citations by year
- 2026: 171 · 2025: 188 · 2024: 172 · 2023: 159 · 2022: 138 · 2021: 153 · 2020: 108 · 2019: 115 · 2018: 86 · 2017: 87 · 2016: 93 · 2015: 79 · 2014: 50 · 2013: 61 · 2012: 26
- FWCI
- 66.24
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Political Analysis (publishedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- Topics
- Social Sciences › Sociology and Political Science › Qualitative Comparative Analysis Research
- Social Sciences › Decision Sciences › Management Science and Operations Research › Fuzzy and Soft Set Theory
- Social Sciences › Political Science and International Relations › Political Science Research and Education
- Keywords
- set-theoretic analysis, fuzzy sets, rough set theory, consistency measure, coverage measures, subset relation, explained variance, partitioning, binary variables, social science methodology
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